Biotechnology/biopharmaceutical companies have found significant commercial success in business methods wherein a biotechnology company partners with a large pharmaceutical company in pursuit of a particular scientific discovery. For example, it is common for biotechnology companies to engage in various discovery processes (e.g. drug “target” discovery processes) whereby they retain downstream intellectual property rights and/or royalty streams. It is also common for biopharmaceutical companies to collaborate with pharmaceutical companies for purposes of drug discovery, wherein the biopharmaceutical companies use one of several methods to identify regions of the genome that play a role in a particular disease.
The DNA that makes up human chromosomes provides the instructions that direct the production of all proteins in the body. These proteins carry out vital functions of life. Variations in DNA are directly related to almost all human diseases, including infectious diseases, cancers, inherited disorders, and autoimmune disorders. Variations in DNA attributing to a phenotypic change, such as a disease or a disorder, may result from a single variation that disrupts the complex interactions of several genes or from any number of mutations within a single gene. For example, Type I and II diabetes have been linked to multiple genes, each with its own pattern of mutations. In contrast, cystic fibrosis can be caused by any one of over 300 different mutations in a single gene. Phenotypic changes may also result from variations in non-coding regions of the genome. For example, a single nucleotide variation in a regulatory region can upregulate or downregulate gene expression or alter gene activity.
Recent technological developments in the field of human genomic have enabled the development of pharmacogenomics, the use of human DNA sequence variability in the development and prescription of drugs. Pharmacogenomics is based on the correlation or association between a given genotype and a resulting phenotype. Since the first correlation study over half-a-century ago linking adverse drug response with amino acid variations in two drug-metabolizing enzymes (plasma cholinesterase and glucose-6-phosphate dehydrogenase), other correlation studies have linked sequence polymorphisms with drug metabolism enzymes, drug targets and drug transporters with compromised levels of drug efficacy or safety.
Pharmacogenomics information is especially useful in clinical settings where correlation information is used to prevent drug toxicities. For example, patients are often screened for genetic differences in the thiopurine methyltransferase gene that cause decreased metabolism of 6-mercaptopurine or azathiopurine. However, only a small percentage of observed drug toxicities have been explained adequately by the set of pharmacogenomic markers available to date. In addition, “outlier” individuals, or individuals experiencing unanticipated effects in clinical trials (when administered drugs that have previously been demonstrated to be both safe and efficacious), cause substantial delays in obtaining FDA drug approval and may even cause certain drugs to come off market, though such drugs may be efficacious for a majority of recipients.
The various biotechnological methods used to date to identify target genomic regions include, for example, differential gene expression which essentially looks for differences in gene expression between control and case samples; protein-protein interaction maps which are used to identify drug receptors and their immediate effectors; and mining human sequence databases for sequences similar to known disease-related, pharmacokinetic or pharmacodynamic regulators. In comparison, association studies that correlate and validate genomic regions with a particular phenotypic trait rely on population genetics and robust statistical metrics. Association studies provide a powerful tool to obtain greater amounts of information in a shorter amount of time thus reducing costs of research and development efforts.
Because all humans are 99.9% identical in their genetic makeup, the DNA sequence of any two individuals is nearly identical. Variations between individuals include, for example, deletions or insertions of DNA sequences, variations in the number of repetitive DNA elements in non-coding regions and changes in a single nitrogenous base position, or “single nucleotide polymorphisms” (SNP). It is estimated that there are 3 to 4 million common SNPs that occur in at least 10 percent of people. These common SNPs do not occur independently but are inherited from generation to generation in tandem with other SNPs, forming patterns across the genome. Such groups of SNPs are referred to as SNP haplotype blocks, or simply haplotypes, herein.
Common SNPs are useful for conducting whole-genome association studies. Whole genomes are scanned of individuals, with and without a phenotypic trait (e.g., resistance to a disease, toxicity from a drug), and correlation is made between SNPs of the case group and a particular phenotypic state. Such whole-genome analyses provide a fine degree of genetic mapping and can pinpoint to specific regions of linkage. Methods for whole genome analysis are described in U.S. Ser. No. 60/327,006, filed Oct. 5, 2001, “Identifying Human SNP Haplotypes, Informative SNPs and Uses Thereof,” assigned to the assignee of the present invention and U.S. Ser. No. 10/106,097 “Methods For Genomic Analysis”, both incorporated herein by reference for all purposes. Further, the identity of SNPs and SNP haplotype blocks across one representative chromosome, e.g. Chromosome 21, are disclosed in U.S. Ser. No., 60/323,059 filed Sep. 18, 2001, “Human Genomic Polymorphisms” assigned to the assignee of the present invention and U.S. Ser. No. 10/284,444 entitled “Human Genomic Polymorphisms”, incorporated herein by reference for all purposes. See also Patil, N. et al, “Blocks of Limited Haplotype Diversity Revealed by High-Resolution Scanning of Human Chromosome 21” Science 294, 1719-1723 (2001), disclosing SNPs and haplotype structure of Chromosome 21.
It is desirable to establish new and useful business methods to capitalize on these technological and scientific developments in genetics.